This case-control study assesses imaging and autopsy data from patients with dementia with Lewy bodies and probable dementia with Lewy bodies to investigate longitudinal change in 18F-fluorodeoxyglucose positron emission tomography.
Key Points
Question
Does brain metabolism assessed with 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) change over time in individuals with prodromal dementia with Lewy bodies (DLB) and probable DLB?
Findings
This longitudinal case-control study with a mean (SD) follow-up of 3.8 (2.3) years found that brain hypometabolism begins to evolve during the prodromal stage of DLB with changes paralleling symptomatic progression.
Meaning
These data may inform use of FDG-PET in clinical practice and trials for biologic staging of DLB, monitoring disease progression, and assessing treatment response.
Abstract
Importance
Although 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established cross-sectional biomarker of brain metabolism in dementia with Lewy bodies (DLB), the longitudinal change in FDG-PET has not been characterized.
Objective
To investigate longitudinal FDG-PET in prodromal DLB and DLB, including a subsample with autopsy data, and report estimated sample sizes for a hypothetical clinical trial in DLB.
Design, Setting, and Participants
Longitudinal case-control study with mean (SD) follow-up of 3.8 (2.3) years. Cases were recruited consecutively between 2007 and 2022 at a referral center and among the population. Patients with probable DLB or mild cognitive impairment with Lewy bodies (MCI-LB) were included. Individuals without cognitive impairment were included from a population-based cohort balanced on age and sex for comparison. All participants completed at least 1 follow-up assessment by design.
Exposure
Patients with MCI-LB and DLB.
Main Outcomes and Measures
Rate of change in FDG-PET was assessed as standardized uptake value ratios (SUVr). Clinical progression was assessed with the Clinical Dementia Rating Sum of Boxes (CDR-SB) score.
Results
Thirty-five patients with probable DLB, 37 patients with MCI-LB, and 100 individuals without cognitive impairment were included. The mean (SD) age of the DLB and MCI-LB groups combined (n = 72) was 69.6 (8.2) years; 66 patients (92%) were men and 6 (8%) were women. At follow-up, 18 participants (49%) with MCI-LB had progressed to probable DLB. Patients with MCI-LB had a faster decline in FDG-SUVr, compared with that of participants without cognitive impairment, in the posterior cingulate, occipital, parietal, temporal, and lateral frontal cortices. The same regions showed greater metabolic decline in patients with DLB than in participants without cognitive impairment, with the addition of anterior-middle cingulate, insula, and medial frontal orbital cortices. Rates of change in FDG-PET in these brain regions were combined into a region of interest (ROI) labeled longitudinal FDG-PET LB meta-ROI. The rate of change in FDG-SUVr in the meta-ROI correlated with the rate of change in CDR-SB, and sample size estimates were reported for potential clinical trials in DLB. Findings were confirmed in the subsample with neuropathologic confirmation (n = 20).
Conclusions and Relevance
This study found that brain hypometabolism begins to evolve during the prodromal stages of DLB with changes paralleling symptomatic progression. These data may inform clinical practice and trials planning to use FDG-PET for biologic staging, monitoring disease progression, and potentially assessing treatment response.
Introduction
Dementia with Lewy bodies (DLB) is the second most common neurodegenerative dementia. Clinically, individuals progress along a continuum primarily driven by α-synuclein–related pathology (ie, the Lewy body [LB] continuum). The LB continuum encompasses the early prodromal stage of isolated rapid eye movement sleep behavior disorder (iRBD),1 the stage of prodromal DLB with clinical impairment reflected by mild cognitive impairment with Lewy bodies (MCI-LB) as the predominant phenotype,2 and the dementia stage of DLB.3
To date, there are no disease-modifying treatments for DLB, although advances in understanding of disease pathophysiology have opened new opportunities for clinical trials. A major advance is the discovery of the biological mechanisms underlying DLB, which can facilitate the targeting of disease-specific processes.4 Second, the approval of disease-modifying treatments for Alzheimer disease (AD) has intensified the interest on clinical trials for AD-related dementias such as DLB,4 including the opportunity to treat AD co-pathology in DLB.5,6 Third, the emergence of seed amplification assays (SAA) for α-synuclein enables an earlier and more accurate diagnosis, helping patient enrichment, target engagement, and assessment of treatment response.5,6,7 Fourth, there has been a revamp of clinical trials at large, with development of innovative trial designs,6 but also new recommendations for outcome measures specific to DLB.8 Finally, there has been important progress in conceptualizing and understanding early clinical stages of DLB, with the development of diagnostic criteria for prodromal DLB2 and iRBD,1 which makes it possible to treat DLB at the prodromal stages.
One of the greatest challenges for clinical trials of DLB is the selection of appropriate outcome measures.8 With the field moving toward a biological definition of Lewy body disease,9,10 biomarkers have the potential to integrate precision medicine into clinical trials.5,6 However, in the current state, α-synuclein SAAs might not be ideal outcome measure for trials, paralleling what researchers have learned from biofluid biomarkers in AD amyloid-β modifying trials.11,12 Two reasons for this is that SAAs have a limited dynamic change over time and the currently available biomarker results being binary (positive vs negative).7 Instead, biomarkers of downstream changes aligning with clinical outcomes may be preferred as outcome measures.11,12 One possibility is neurofilament light chain (NfL) as a marker of neuronal-axonal injury.13 However, NfL also changes in non-DLB neurodegenerative diseases and in traumatic, inflammatory, and vascular conditions.13 Opposite to NfL, topographical neuroimaging markers have the advantage of informing disease staging and spatial progression of neurodegeneration. DaTscan is an indicative neuroimaging marker of both DLB and prodromal DLB.2,3 However, DaTscan may be negative in a subset of patients with autopsy-confirmed DLB,14 and requiring a positive DaTscan may lead to recruitment of patients with DLB with a more parkinsonian phenotype.5 Furthermore, the sensitivity of DaTscan is currently low for prodromal DLB.15 In contrast,18F-fluorodeoxyglucose positron emission tomography (FDG-PET) shows early abnormalities in iRBD,16 and cross-sectional studies suggest that it may continue to change during MCI-LB and DLB,15,17,18,19,20 thus offering the topographical dimension with an optimal dynamic range of change. While most outcome measures used in previous DLB clinical trials are not disease-specific nor validated for DLB,4 FDG-PET is established and widely used as a supportive biomarker for the clinical diagnosis of DLB and MCI-LB, with relevance for the differential diagnosis with AD.3
The current barrier for FDG-PET as a disease progression outcome for DLB clinical trials is the lack of scientific evidence from longitudinal studies. Several cross-sectional studies reported baseline FDG-PET patterns in patients with MCI-LB who progressed to DLB or other dementias or remained clinically stable at follow-up.18,19,20,21,22,23,24,25 However, no study has characterized the topographical changes and longitudinal rate of change of FDG-PET in MCI-LB or DLB, which is a priority for DLB clinical trials.26 A longitudinal FDG-PET study in 5 patients with Parkinson disease who developed dementia (PDD) within 2 years reported significant metabolic decline on FDG-PET with most prominently changes in caudate, thalamus, and posterior cingulate cortex.27
The goal of the current study was to investigate longitudinal FDG-PET in MCI-LB and DLB. We report regional changes in FDG-PET and the well-established DLB biomarker cingulate island sign (CIS),3 and demonstrate associations with disease progression. We propose a meta region of interest as it may provide additional value in diagnostic clarification and participant stratification for clinical trials. We estimate sample sizes for a hypothetical clinical trial and report longitudinal FDG-PET changes in a subsample with neuropathologic confirmation of Lewy body disease.
Methods
Participants and Procedures
The Mayo Clinic institutional review board approved the study. Informed consent on participation was obtained from all patients or a surrogate according to the Declaration of Helsinki. We followed EQUATOR reporting guidelines.
We included consecutive patients with probable DLB3 or MCI-LB2 from the Mayo Clinic Alzheimer Disease Research Center and the Longitudinal Imaging Biomarkers of Prodromal DLB and DLB Program (ie, DLB Spectrum study) (September 2007 to August 2022). We also included 100 CU individuals from the Mayo Clinic Study of Aging28 through frequency matching on age and sex. All individuals without cognitive impairment remained without cognitive impairment during the follow-up.
We excluded individuals with neurological or psychiatric disorders other than MCI-LB and DLB (eMethods in Supplement 1 for further details). Clinical diagnosis was established on consensus by behavioral neurologists, neuropsychologists, and study coordinators, as explained elsewhere.20,29
PET images were acquired on PET/computed tomography scanners (GE Healthcare and Siemens) and T1-weighted magnetic resonance images on 3T scanners (GE Healthcare and Siemens).20 Scans were inspected for quality. We analyzed FDG-PET images with the pipeline described in the eMethods in Supplement 1. We estimated standardized uptake value ratio (SUVr) values referenced to the pons across brain regions listed in eTable 1 in Supplement 1. To reduce the number of statistical models, regions from the in-house modified Automated Anatomical Labeling atlas were combined into 15 regions of interest (ROIs) according to anatomical and functional knowledge (eTable 1 in Supplement 1).
For the autopsy data, brains were sectioned and sampled using standard protocols30,31 and evaluated as detailed in the eMethods in Supplement 1. Cases were classified into (1) high likelihood DLB,30 (2) high likelihood AD,24,27 and (3) Lewy body disease with AD co-pathology.32
Statistical Analyses
Group differences were tested with analysis of variance for continuous variables and χ2 tests for categorical variables. Linear regression analysis was performed on baseline measurements for each ROI. Models were adjusted for age with patient group as the covariant of interest and individuals without cognitive impairment as the reference group. Group P values are reported along with the adjusted overall group false discovery rate (FDR)33 q values.
Longitudinal FDG-PET rates of change were investigated through linear mixed-effects models separate for each of the 15 ROIs. Models were adjusted for baseline age and included a group term and group × time interaction. No cognitive impairment was the reference group, with additional models with DLB as the reference group to test for direct differences between MCI-LB and DLB. We report uncorrected P values, and statistical significance was confirmed using the FDR method.
Associations between longitudinal change in FDG-SUVr with disease progression were investigated through partial Pearson correlations with age as a covariate. For this analysis, individual slopes were calculated using linear regression for FDG-SUVr and the Clinical Dementia Rating Sum of Boxes (CDR-SB) as a proxy for disease progression.
Finally, we estimated sample sizes for a hypothetical clinical trial to slow down neurodegeneration in patients with DLB. Using slope estimates and variances from mixed models, we estimated sample sizes with jackknife resampling to produce confidence intervals. Change in regional FDG-PET SUVr relative to controls was used for these calculations, for 25% and 50% reduction in slope, assuming 1-sided tests, 80% power, α = .05, and readings at 12, 18, 24, and 36 months of follow-up.
Results
Cohort Characteristics
A total of 172 individuals met selection criteria: 37 with MCI-LB, 35 with probable DLB, 100 without cognitive impairment (Table 1). Participants completed between 2 and 8 FDG-PET visits with a mean (SD) follow-up time of 3.8 (2.3) years. All visits were included as data in the mixed-effects models. Eighteen patients with MCI-LB (49%) progressed to probable DLB, and 19 patients (51%) remained stable as MCI-LB over the course of the study. One patient with MCI-LB had a cerebral infarction before progressing to probable DLB at follow-up.
Table 1. Cohort Characteristics.
| Characteristic | No. (%) | P value | ||
|---|---|---|---|---|
| No impairment (n = 100) | MCI-LB (n = 37) | DLB (n = 35) | ||
| Age, mean (SD), y | 67.6 (9.1) | 69.4 (7.8) | 68.8 (8.8) | .54 |
| Sex | ||||
| Males | 90 (90) | 35 (95) | 31 (89) | .63 |
| Females | 10 (10) | 2 (5) | 4 (11) | |
| Education, mean (SD), y | 15.7 (2.6) | 16.1 (3.0) | 15.8 (3.2) | .73 |
| CDR-SB, mean (SD) | 0.0 (0.1) | 1.6 (0.9) | 4.1 (1.5) | <.001 |
| MMSE score, mean (SD) | 28.9 (1.0) | 27.2 (2.2) | 23.6 (4.6) | <.001 |
| APOE genotype, ≥1 ε4 allele | 29 (29) | 12 (32) | 14 (40) | .49 |
| Visual hallucinations | NA | 7 (19) | 21 (60) | <.001 |
| Cognitive fluctuations | NA | 10 (27) | 27 (77) | <.001 |
| Parkinsonism | NA | 29 (78) | 32 (91) | .12 |
| Probable RBD | NA | 34 (92) | 35 (100) | .09 |
| Follow-up time, mean (SD), y | 4.5 (2.3) | 3.4 (2.2) | 2.3 (1.3) | <.001 |
| No. of visits, mean (SD) | 2.4 (0.6) | 3.4 (1.5) | 2.9 (1.1) | <.001 |
| MCI-LB, clinical diagnosis at FDG-PET follow-up | ||||
| Stable MCI-LB | NA | 19 (51) | NA | |
| Progression to dementia | NA | 18 (49) | NA | |
| Probable DLB, No. (% of dementia) | NA | 18 (100) | NA | |
| Longitudinal change in CDR-SB, mean (SD) | −0.00 (0.01) | 0.58 (0.76) | 1.54 (2.05) | <.001 |
Abbreviations: APOE, apolipoprotein E; CDR-SB, Clinical Dementia Rating Sum of Boxes; DLB, dementia with Lewy bodies; FDG-PET, 18F-fluorodeoxyglucose positron emission tomography; MCI-LB, mild cognitive impairment with Lewy bodies; MMSE, Mini-Mental State Examination; NA, not applicable; RBD, rapid eye movement sleep behavior disorder.
FDG-PET Group Differences at Baseline
Figure 1A and eFigure 1 in Supplement 1 show FDG-SUVr across groups at baseline, including estimates for group differences. Both MCI-LB and DLB showed statistically significantly lower FDG-SUVr compared with no cognitive impairment with the strongest estimates observed in occipital, parietal, and lateral temporal regions, extending to frontal areas, thalamus, and substantia nigra. The DLB group also showed statistically significantly lower FDG-SUVr in temporal pole and primary sensory areas than the group without cognitive impairment. Findings survived the FDR adjustment.
Figure 1. Summary Findings for the Groups Mild Cognitive Impairment With Lewy Bodies (MCI-LB) and Dementia With Lewy Bodies (DLB).
A, Cross-sectional 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) differences in standardized uptake value ratios (SUVr) based on linear regression adjusting for age. Blue denotes statistically significant regions of interest (ROIs) for MCI-LB compared with individuals without cognitive impairment while red denotes statistically significant ROIs for DLB compared with no cognitive impairment. All results survived the false discovery rate (FDR) adjustment. B, Longitudinal FDG-PET rate of change based on mixed-effects models. Blue denotes statistically significant ROIs for the MCI-LB × time interaction (MCI-LB having a faster rate of change than no cognitive impairment). Red denotes statistically significant ROIs for the DLB × time interaction with no cognitive impairment as the reference group (DLB having a faster rate of change than no cognitive impairment), while brown denotes statistically significant ROIs for the DLB × time interaction with MCI-LB as the reference group (DLB having a faster rate of change than MCI-LB). The uncorrected P = .03 for the lateral frontal region in MCI-LB vs no cognitive impairment became q = 0.056 when FDR adjusted; otherwise, all results for MCI-LB vs no cognitive impairment and DLB vs no cognitive impairment survived the FDR adjustment. Results for DLB vs MCI-LB did not survive the FDR adjustment. C, The longitudinal FDG-PET LB meta-ROI includes ROIs that were statistically significant (FDR adjusted) for both MCI-LB and DLB groups based on their interaction term with time in mixed-effects models (see Table 1). D, Predicted curve for the FDG-PET rate of change for the longitudinal FDG-PET LB meta-ROI from mixed-effects models. E, Scatterplot for the partial Pearson correlation for FDG-PET rate of change with Clinical Dementia Rating Sum of Boxes (CDR-SB) rate of change for the longitudinal FDG LB meta-ROI.
Longitudinal FDG-PET Rate of Change
Table 2 and eFigure 2 in Supplement 1 show the results from the mixed-effects models for longitudinal FDG-PET rate of change in MCI-LB and DLB compared with no cognitive impairment, and Figure 1B summarizes the findings including model estimates.
Table 2. Mixed-Effects Model for FDG-PET in Study Groups by Time Controlling for Agea.
| ROI | Intercept | Time | Age | MCI-LB | DLB | MCI-LB × timea | DLB × timea | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Est (SE) | P value | Est (SE) | P value | Est (SE) | P value | Est (SE) | P value | Est (SE) | P value | Est (SE) | P value | Est (SE) | P value | |
| Amygdala | 1.201 (0.029) | <.001 | 0.001 (0.001) | .34 | −0.021 (0.004) | <.001 | 0.020 (0.010) | .04 | 0.013 (0.010) | .19 | −0.001 (0.002) | .36 | −0.002 (0.002) | .33 |
| Anterior-middle cingulate | 1.712 (0.046) | <.001 | −0.006 (0.001) | <.001 | −0.050 (0.007) | <.001 | 0.006 (0.015) | .69 | −0.007 (0.015) | .67 | −0.001 (0.003) | .64 | −0.007 (0.004) | .04 |
| Basal ganglia | 1.815 (0.057) | <.001 | −0.008 (0.002) | <.001 | −0.034 (0.008) | <.001 | 0.001 (0.018) | .96 | −0.027 (0.018) | .15 | 0.001 (0.004) | .73 | −0.005 (0.005) | .33 |
| Inferior temporal | 1.777 (0.057) | <.001 | −0.009 (0.001) | <.001 | −0.040 (0.008) | <.001 | −0.092 (0.018) | <.001 | −0.178 (0.019) | <.001 | −0.011 (0.003) | <.001 | −0.014 (0.003) | <.001 |
| Insula | 1.820 (0.045) | <.001 | −0.007 (0.001) | <.001 | −0.062 (0.007) | <.001 | −0.001 (0.015) | .92 | −0.030 (0.015) | .05 | −0.003 (0.002) | .23 | −0.009 (0.003) | .007 |
| Lateral frontal | 1.987 (0.072) | <.001 | −0.010 (0.002) | <.001 | −0.053 (0.010) | <.001 | −0.097 (0.023) | <.001 | −0.183 (0.024) | <.001 | −0.008 (0.004) | .03 | −0.023 (0.005) | <.001 |
| Lateral temporal | 1.788 (0.06) | <.001 | −0.008 (0.001) | <.001 | −0.043 (0.009) | <.001 | −0.106 (0.019) | <.001 | −0.211 (0.019) | <.001 | −0.011 (0.003) | <.001 | −0.018 (0.004) | <.001 |
| Medial frontal orbital | 1.828 (0.058) | <.001 | −0.009 (0.002) | <.001 | −0.044 (0.008) | <.001 | −0.075 (0.019) | <.001 | −0.121 (0.019) | <.001 | −0.004 (0.003) | .20 | −0.017 (0.004) | <.001 |
| Medial temporal | 1.421 (0.036) | <.001 | −0.003 (0.001) | <.001 | −0.035 (0.005) | <.001 | 0.008 (0.012) | .47 | −0.018 (0.012) | .14 | −0.005 (0.002) | .006 | −0.007 (0.002) | .003 |
| Occipital | 1.909 (0.084) | <.001 | −0.011 (0.002) | <.001 | −0.039 (0.012) | .002 | −0.180 (0.027) | <.001 | −0.286 (0.027) | <.001 | −0.011 (0.004) | .003 | −0.016 (0.005) | .001 |
| Parietal | 1.946 (0.082) | <.001 | −0.010 (0.002) | <.001 | −0.050 (0.012) | <.001 | −0.183 (0.026) | <.001 | −0.314 (0.027) | <.001 | −0.010 (0.003) | .003 | −0.017 (0.004) | <.001 |
| Posterior cingulate | 2.299 (0.090) | <.001 | −0.013 (0.002) | <.001 | −0.063 (0.013) | <.001 | −0.146 (0.029) | <.001 | −0.279 (0.029) | <.001 | −0.022 (0.005) | <.001 | −0.034 (0.007) | <.001 |
| Primary sensory motor | 1.752 (0.056) | <.001 | −0.008 (0.001) | <.001 | −0.034 (0.008) | <.001 | −0.035 (0.018) | .06 | −0.068 (0.019) | <.001 | 0.002 (0.003) | .48 | −0.008 (0.004) | .05 |
| Substantia nigra | 1.136 (0.035) | <.001 | −0.004 (0.001) | <.001 | 0.007 (0.005) | .19 | −0.047 (0.012) | <.001 | −0.060 (0.012) | <.001 | 0 (0.002) | .85 | −0.003 (0.003) | .30 |
| Temporal pole | 1.460 (0.036) | <.001 | −0.003 (0.001) | <.001 | −0.043 (0.005) | <.001 | −0.002 (0.012) | .89 | −0.033 (0.012) | .007 | −0.004 (0.002) | .009 | −0.008 (0.002) | <.001 |
| Thalamus | 1.591 (0.043) | <.001 | −0.010 (0.001) | <.001 | −0.014 (0.006) | .03 | −0.062 (0.014) | <.001 | −0.090 (0.015) | <.001 | −0.002 (0.003) | .57 | −0.006 (0.004) | .19 |
| Longitudinal FDG-PET LB meta-ROI | 1.828 (0.064) | <.001 | −0.009 (0.001) | <.001 | −0.043 (0.009) | <.001 | −0.130 (0.020) | <.001 | −0.230 (0.021) | <.001 | −0.010 (0.003) | <.001 | −0.015 (0.004) | <.001 |
| CIS | 1.152 (0.043) | <.001 | −0.000 (0.001) | .66 | −0.007 (0.006) | .29 | 0.046 (0.014) | .002 | 0.036 (0.015) | .01 | −0.007 (0.002) | .001 | −0.010 (0.003) | <.001 |
Abbreviations: CIS, cingulate island sign; DLB, dementia with Lewy bodies; Est, estimate from mixed-effects models; FDG-PET, 18F-fluorodeoxyglucose positron emission tomography; FDR, false discovery rate; MCI-LB, mild cognitive impairment with Lewy bodies; ROI, region of interest.
Models were built with no cognitive impairment as the reference group. All significant P values in MCI-LB × time and DLB × time interactions survived the FDR adjustment except for the lateral frontal region for the MCI-LB × time interaction, which changed from an uncorrected P = .03 to an FDR-adjusted q = 0.056, and the anterior-middle cingulate region for the DLB × time interaction, which changed from an uncorrected P = .04 to an FDR-adjusted q = 0.052. The longitudinal FDG-PET LB meta-ROI includes the ROIs that were statistically significant (FDR adjusted) for both MCI-LB and DLB based on their interaction term with time as follows: inferior temporal, lateral temporal, medial temporal, occipital, parietal, posterior cingulate, and temporal pole.
When compared with change among those without cognitive impairment, the MCI-LB group showed a statistically significantly faster FDG-SUVr rate of decline in the posterior cingulate, occipital, lateral temporal, inferior temporal, parietal, lateral frontal, medial temporal, and temporal pole cortices. The same regions showed a statistically significantly faster FDG-SUVr rate of decline in DLB when compared with no cognitive impairment, with the addition of faster FDG-SUVr rate of decline in insula, medial frontal orbital cortex, and anterior-middle cingulate. The FDR adjustment did not change these results apart from lateral frontal in MCI-LB and anterior-middle cingulate in DLB reaching q = 0.056 and q = 0.052, respectively.
We next created the longitudinal FDG-PET LB meta-ROI by combining the regions that were statistically significant for both MCI-LB and DLB (Figure 1C). The mixed-effects model for this meta-ROI showed a statistically significantly faster FDG-SUVr rate of decline in both MCI-LB and DLB than in individuals without cognitive impairment (Table 2 and Figure 1D).
Based on these results, we observed that rates of change in specific regions were different for MCI-LB and DLB. Therefore, we compared the change estimates of DLB to the MCI-LB group. The FDG-PET rate of decline was faster in patients with DLB compared with MCI-LB in the lateral frontal (estimate, −0.015; SE, 0.028; P = .006), medial frontal orbital (−0.013; SE, 0.023; P = .01), and primary sensory motor cortex (−0.010; SE, 0.022; P = .03). However, this finding was not reflected in the longitudinal FDG-PET LB meta-ROI (−0.005; SE, 0.025; P = .21). These results for DLB vs MCI-LB did not survive the FDR adjustment.
For the CIS, both the MCI-LB and DLB groups showed a statistically significantly faster FDG-PET rate of change than individuals without cognitive impairment (Table 2), with no differences between MCI-LB and DLB (−0.002; SE, 0.003; P = .47).
Association of Longitudinal FDG-PET Rate of Change With Disease Progression
We then investigated the association between rate of change in FDG-SUVr and disease progression as reflected by the rate of change in CDR-SB while controlling for age. This analysis was performed in the MCI-LB and DLB groups only, combining them into 1 single group. A faster decline in FDG-SUVr correlated with a faster increase in CDR-SB (reflecting increased disease severity) across all ROIs (eFigure 3 in Supplement 1). A faster decline in FDG-SUVr in the meta-ROI also correlated with a faster increase in CDR-SB (Figure 1E).
Neuropathologic Confirmation
A neuropathologic examination was available for 22 cases (7 MCI-LB and 15 DLB). Cases were classified into Lewy body disease (LBD, n = 12, of whom 2 also had primary age-related tauopathy), mixed Lewy body disease with AD (LBD+AD, n = 8), and no Lewy body disease (n = 2; where 1 patient had AD and 1 had progressive supranuclear palsy, both being clinically diagnosed with DLB at the baseline FDG-PET examination). Therefore, 20 neuropathologically confirmed cases (91%) had LBD-related pathology (eTable 2 in Supplement 1).
When compared with individuals without cognitive impairment, the LBD group showed a statistically significant faster decline in FDG-SUVr in the lateral frontal, medial frontal orbital, lateral temporal, medial temporal, and posterior cingulate cortices (estimates in eTable 3 in Supplement 1). Because of the small sample size (n = 10), none of these findings survived the FDR adjustment, although the results for the lateral frontal cortex changed from an uncorrected P = .003 to an FDR-adjusted q = 0.055. When compared with no cognitive impairment, LBD+AD cases (n = 8) showed a statistically significant faster FDG-PET rate of change in all ROIs except for the amygdala and substantia nigra (eTable 3 in Supplement 1). All of the findings for the LBD+AD group survived the FDR adjustment.
The meta-ROI showed a statistically significantly faster rate of decline in FDG-SUVr in the LBD+AD group compared with no cognitive impairment (Figure 2), although this did not reach statistical significance for the LBD group (−0.009; SE, 0.005; P = .07).
Figure 2. Longitudinal 18F-Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) Rate of Change in Participants With Neuropathologic Confirmation of Lewy Body Disease (LBD) at Autopsy.
Predicted curve for the FDG-PET rate of change in the longitudinal FDG-PET Lewy body meta–region of interest from mixed-effects models. LBD+AD indicates mixed Lewy body disease and Alzheimer disease at autopsy; SUVr, standardized uptake value ratios.
Sample Size Estimates for a Hypothetical Clinical Trial in DLB
Table 3 shows sample size estimates based on FDG-PET, CDR-SB, and Mini-Mental State Examination (MMSE) score. Using the longitudinal FDG-PET LB meta-ROI required substantially fewer individuals for 25% and 50% reductions in slopes across all follow-up time intervals (12, 18, 24, and 36 months), in comparison with using clinical measures such as CDR-SB or MMSE score.
Table 3. Sample Size Estimates for Hypothetical Clinical Trials in DLBa.
| Value | Follow-up point | |||||||
|---|---|---|---|---|---|---|---|---|
| 12 mo | 18 mo | 24 mo | 36 mo | |||||
| Δ Change in longitudinal FDG-PET LB meta-ROI measure/effect size, % | 25 | 50 | 25 | 50 | 25 | 50 | 25 | 50 |
| No. of individuals (95% CI) | 303 (255-352) | 77 (66-87) | 135 (115-156) | 34 (29-39) | 76 (65-88) | 19 (16-22) | 34 (29-39) | 9 (8-10) |
| Δ Change in CDR-SB measure/effect size, % | 25 | 50 | 25 | 50 | 25 | 50 | 25 | 50 |
| No. of individuals (95% CI) | 668 (583-752) | 168 (147-188) | 297 (260-334) | 75 (66-84) | 168 (147-189) | 42 (37-47) | 75 (66-84) | 19 (17-21) |
| Δ Change in MMSE score measure/effect size, % | 25 | 50 | 25 | 50 | 25 | 50 | 25 | 50 |
| No. of individuals (95% CI) | 1217 (969-1466) | 305 (244-366) | 540 (429-651) | 135 (109-162) | 305 (242-367) | 76 (61-91) | 136 (108-163) | 34 (27-41) |
Abbreviations: CDR-SB, Clinical Dementia Rating Sum of Boxes; DLB, dementia with Lewy bodies; Δ, annualized rate of change; FDG-PET, 18F-fluorodeoxyglucose positron emission tomography; FDR, false discovery rate; LB, Lewy bodies; MCI-LB, mild cognitive impairment with Lewy bodies; MMSE, Mini-Mental State Examination; ROI, region of interest.
Slope estimates and variances were obtained using mixed models. The 25% or 50% reduction in slope is relative to individuals without cognitive impairment. Total sample sizes were estimated using jackknife resampling to produce 95% CIs, with 80% power, and readings at 12, 18, 24, and 36 months. The calculated sample sizes are for clinical trials with 50% of the participants treated and 50% not treated. The longitudinal FDG-PET LB meta-ROI includes the ROIs that were statistically significant (FDR adjusted) for both MCI-LB and DLB based on their interaction term with time, as follows: inferior temporal, lateral temporal, medial temporal, occipital, parietal, posterior cingulate, and temporal pole (see Table 2).
Discussion
We investigated longitudinal FDG-PET in MCI-LB and DLB with a mean (SD) follow-up time of 2.9 (1.9) years. Cross-sectional analyses at baseline confirmed the previously described signature pattern of FDG-PET hypometabolism in DLB and MCI-LB.2,3,15,34,35 We demonstrated significant hypometabolism in characteristic occipital, parietal, and lateral temporal regions, extending to frontal areas, primary sensory motor areas, thalamus, and substantia nigra. This analysis also helped establish baseline results for the interpretation of longitudinal findings on rate of change. Specifically, patients with MCI-LB had a faster decline in FDG metabolism on PET than individuals without cognitive impairment in the posterior cingulate and occipital, parietal, temporal, and lateral frontal cortices. This suggests that areas such as substantia nigra and thalamus become hypometabolic early in the LB continuum, before the clinical onset of MCI-LB, but do not continue to change during the progression of MCI-LB and DLB. Indeed, our recent FDG-PET study in iRBD16 showed early hypometabolism in substantia nigra and thalamus, together with early hypometabolism in the retrosplenial and angular cortices. Our current study shows that FDG-PET in retrosplenial and angular cortices (included in our parietal ROI) continues to change in MCI-LB and DLB. The posterior cingulate region is anatomically close to retrosplenial cortex. While hypometabolism has not been demonstrated in the posterior cingulate in iRBD,16 our current data show that the posterior cingulate had the highest rate of change in MCI-LB and DLB.
Cross-sectionally at baseline, the posterior cingulate was among the 3 ROIs with the greatest difference estimates, with the parietal ROI that includes the retrosplenial cortex and the occipital ROI showing greater difference estimates. The ratio between posterior cingulate and adjacent retrosplenial, parietal, and occipital ROIs defines the supportive CIS biomarker.36 Our data suggest that cross-sectionally the CIS emerges because hypometabolism in retrosplenial, parietal, and occipital ROIs is greater in relation to hypometabolism in the posterior cingulate across iRBD, MCI-LB, and DLB stages and because hypometabolism affects retrosplenial cortex earlier than the posterior cingulate cortex. However, we demonstrate that, longitudinally, posterior cingulate has a faster rate of change than adjacent retrosplenial, parietal, and occipital ROIs. Still, a faster rate of change of posterior cingulate does not mitigate its preservation relative to retrosplenial, parietal, and occipital ROIs; hence, the CIS continues to emerge cross-sectionally. This interpretation was supported by our longitudinal analysis showing that the CIS ratio has a faster rate of change in both MCI-LB and DLB compared with no cognitive impairment, but there were no significant differences between MCI-LB and DLB in rate of change of the CIS. Altogether, our data suggest that parietal, occipital, and posterior cingulate ROIs have an excellent dynamic range of change to monitor disease progression along the entire LB continuum and assess response to treatment in clinical trials. Together with our earlier cross-sectional FDG-PET findings in iRBD,16 retrosplenial metabolism may be more sensitive to the disease stage of iRBD and posterior cingulate may be more sensitive to the disease stage of MCI-LB and DLB. Identifying biomarkers that provide full coverage of the disease continuum is crucial, given the increased awareness about MCI-LB in clinical settings.4
Patients with DLB and MCI-LB showed faster decline in FDG-PET in similar regions when compared with individuals without cognitive impairment, with exception of the insula and several frontal lobe ROIs that only declined in the DLB group. This finding possibly delineates the full development of the neurodegenerative process at advanced stages of the disease, outlining the canonical spread of Lewy-related pathology as described in the Braak scheme.37 The specific analysis for DLB with MCI-LB as the reference group supports this idea, showing that FDG-PET metabolism declines faster during the transition from MCI-LB to DLB in several frontal ROIs, all of which are known to be involved during the late Braak stages.37 The involvement of frontal ROIs may be one of the factors underlying the decline in abilities of daily living, which foreshadows the clinical transition from MCI-LB to DLB. Therefore, our data suggest that FDG-PET not only closely tracks the neurodegenerative process along the LB continuum with a remarkable dynamic range and an advantageous topographical characterization of neurodegeneration, but it may also be a surrogate marker of transitions across clinical stages of the disease, which may have implications for clinical use. This is further supported by the correlation between the rate of metabolic decline on FDG-PET and disease progression on CDR-SB, a widely used outcome measure in clinical trials.8 Again, posterior cingulate cortex emerged as an important region, showing the highest correlation coefficient with CDR-SB among all 16 ROIs. Several studies demonstrated that FDG-PET at baseline in DLB correlates with disease progression.17,29,38 Our current study further demonstrates this correlation longitudinally, which may have implications for trials and the clinical management of the disease along the LB continuum, beyond what is already known from cross-sectional studies.
The findings for amygdala and basal ganglia deserve attention. We did not observe hypometabolism in both ROIs in MCI-LB and DLB, cross-sectionally or longitudinally, nor in participants with Lewy body disease. The amygdala showed hypermetabolism in iRBD in a previous study,16 suggesting hyperexcitability due to lack of inhibition from cells in the brainstem; microglial inflammatory-driven increase glucose uptake; and/or response to early neurodegeneration either as a compensatory mechanisms or as a maladaptive, detrimental event. Also, hypermetabolism in amygdala was associated with nigrostriatal dopaminergic deficiency and clinical progression.16 While basal ganglia was not hypermetabolic in our previous study in iRBD, hypermetabolism in the pallidum was associated with lower dopamine transporter availability in the putamen.16 Therefore, it would be interesting to compare our FDG-PET findings with longitudinal DaTscan dynamics, which may reveal how neurodegeneration in basal ganglia relates to glucose metabolism and disease progression along the LB continuum. The autopsy data in a subset of patients largely confirmed all the results from the full cohort. A previous longitudinal FDG-PET study in 5 patients with PDD reported significant FDG-PET changes most prominently in caudate, thalamus, and posterior cingulate cortex.27 Hence, longitudinal FDG-PET changes in posterior cingulate cortex seem to be prominent and shared between DLB and PDD, while the profile of changes seems to be predominantly subcortical in PDD and predominantly cortical in DLB. These differences should be further explored for the clinical use of FDG-PET in the differential diagnosis of DLB and PDD.
Longitudinal biomarkers for clinical trials are currently lacking in DLB. Ideal biomarkers should be tailored to the type of trial (ie, symptomatic vs disease-modifying) and stage of the disease (eg, iRBD, MCI-LB, and mild to moderate DLB).8 The current study, together with recent data on iRBD,16 demonstrates that FDG-PET may serve as a biomarker of disease progression. We provide insights and discuss the use of different ROIs at different stages of the LB continuum. We further investigated and discuss longitudinal change in the supportive biomarker cingulate island sign, and we propose a longitudinal FDG-PET LB meta-ROI that summarizes the changes along the LB continuum, with a good dynamic range of change and correlation with disease progression. While a meta-ROI will generally not perform better than the best performing individual ROIs discussed above, it provides additional value to trials and clinical practice as a more stable outcome measure than individual ROIs. Establishing meta-ROIs for amyloid-β and tau PET ligands have catapulted the research and clinical practice in AD. We encourage future studies to test the proposed meta-ROI in independent cohorts. Meta-ROIs can help increase effect sizes while decreasing participant heterogeneity, sample sizes, and costs of clinical trials. In this study, we provided estimates of the sample sizes needed for 25% and 50% reductions in slope within 36 months in patients with DLB. We demonstrated that our meta-ROI would require substantially smaller trials in comparison with CDR-SB or MMSE score.
Limitations
The main limitation of our current study is the low statistical power of the autopsy-confirmed subsample, although its size was enough to largely confirm the results from the clinically diagnosed cohort. In the future, SAAs will help determine synucleinopathy in vivo, but this assay was not available in our cohort. Our cohort is primarily a midwestern cohort from the United States with limited racial and ethnic diversity. Therefore, generalizability may be limited to the source population. Furthermore, while we present the first dataset with longitudinal FDG-PET in patients with MCI-LB and DLB, including patients with iRBD would have enabled a characterization of the entire LB continuum. As we are not aware of any longitudinal iRBD dataset available for FDG-PET, we mitigated this limitation by discussing our current data against our recent cross-sectional FDG-PET study on iRBD.16
Conclusions
The brain hypometabolism on FDG-PET begins early in prodromal DLB and declines dynamically paralleling disease progression in DLB. These data may inform clinical trials planning to use FDG-PET as a surrogate marker of treatment response. Importantly, FDG-PET may be a contributing biomarker of neurodegeneration in the new staging systems of LBD-associated clinical phenotypes,9,10 and the data reported in this study may facilitate operationalizing those systems in the clinical setting for biological staging of patients and monitoring of disease progression.
eMethods
eReferences
eTable 1. Regions of interest in original atlases and combined regions for the current study
eTable 2. Key characteristics at clinical visit the closest to death for participants with neuropathologic confirmation of LBD
eTable 3. Mixed effects model for FDG-PET in participants with neuropathologic confirmation (controlling for age)
eFigure 1. FDG-PET group differences at baseline
eFigure 2. Longitudinal FDG-PET rate of change
eFigure 3. Association of longitudinal FDG-PET rate of change with disease progression
Data sharing statement
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
eMethods
eReferences
eTable 1. Regions of interest in original atlases and combined regions for the current study
eTable 2. Key characteristics at clinical visit the closest to death for participants with neuropathologic confirmation of LBD
eTable 3. Mixed effects model for FDG-PET in participants with neuropathologic confirmation (controlling for age)
eFigure 1. FDG-PET group differences at baseline
eFigure 2. Longitudinal FDG-PET rate of change
eFigure 3. Association of longitudinal FDG-PET rate of change with disease progression
Data sharing statement